New metrics for evolving risks to human and wildlife health
Abstract/Contents
- Abstract
- Humans are altering the global environment at a rapid pace, which impacts ecosystems and creates opportunities for the spread of infectious diseases to new species. Healthy ecosystems are often dependent on healthy human populations and vice versa. However, resolving risks to human and wildlife populations requires insights provided by a scale of data that is not often available. New modeling approaches can be used to maximize the use of available data to achieve critical insights. In this dissertation, my collaborators and I develop new analytical and statistical approaches to understand the magnitude of risks to the health of human or wildlife populations and provide practical knowledge to mitigate those risks. We first examine the seasonal risk of spillover of a pathogenic acanthocephalan parasite to southern sea otters, which we find is driven by intermediate host population dynamics and sea otter foraging behavior. Then, we investigate the relationship between the genome sizes of viruses and their potential to spillover into new species by comparing the genomes of zoonotic and non-zoonotic viruses. We find that larger genomes increase spillover risk. The risk of death from viruses is difficult to discern due to incomplete sampling of affected individuals. We develop a statistical method to calculate the true risk of death for COVID-19 across countries and find this risk in the early stages of the pandemic was approximately 1\%. Lastly, we investigate through a diverse set of population genetic and epidemiological modeling how emerging gene drive technology can mitigate human risk to schistosomiasis. We find that schistosomiasis can be reduced under select conditions, such as low selfing rate in snail intermediate hosts. Together these chapters demonstrate how to leverage new quantitative approaches to guide conservation and disease management decisions, each important aspects of human and wildlife health.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Grewelle, Richard Ernest |
|---|---|
| Degree supervisor | De Leo, Giulio A |
| Thesis advisor | De Leo, Giulio A |
| Thesis advisor | Lowe, Christopher, (Associate professor of biology) |
| Thesis advisor | Miller, Melissa |
| Thesis advisor | Mordecai, Erin |
| Thesis advisor | Pringle, John R, 1943- |
| Degree committee member | Lowe, Christopher, (Associate professor of biology) |
| Degree committee member | Miller, Melissa |
| Degree committee member | Mordecai, Erin |
| Degree committee member | Pringle, John R, 1943- |
| Associated with | Stanford University, Department of Biology |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Richard Ernest Grewelle IV. |
|---|---|
| Note | Submitted to the Department of Biology. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/nh884fc0836 |
Access conditions
- Copyright
- © 2022 by Richard Ernest Grewelle
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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